ArticleMedical education2025
Artificial intelligence and gender equity: An integrated approach for health professional education.
Article in Medical education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial intelligence for affective-domain development in healthcare professions education: a systematic review.Frontiers in medicine · 2026Pooled it
- Artificial intelligence literacy and related factors among nursing undergraduates in Northeast China.BMC nursing · 2026Article
- Seeing Is Believing? Exploring Gender Bias in Artificial Intelligence Imagery of Specialty Doctors.The clinical teacher · 2026Article
- Latent profile analysis of artificial intelligence anxiety among undergraduate nursing students: a cross-sectional study.Frontiers in public health · 2026Article
- (Dis)embodiment and medical education: How feminist organizational theories can help us think differently about gender.Medical education · 2025Article
- Artificial intelligence and gender equity: An integrated approach for health professional education.Medical education · 2025Article
- Digital Twins for Personalized Medicine Require Epidemiological Data and Mathematical Modeling: Viewpoint.Journal of medical Internet research · 2025Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionAs artificial intelligence (AI) increasingly integrates into health workplaces, evidence suggests AI can exacerbate gender inequity. Health professional programmes have a role to play in ensuring graduates grasp the challenges facing working in an AI-mediated world. APPROACH: Drawing from feminist scholars and empirical evidence, this conceptual paper synthesises current and future ways in which AI compounds gender inequities and, in response, proposes foci for an integrated approach to teaching about AI and equity. ANALYSIS: We propose three concerns. Firstly, multiple literature reviews suggest that the gender divide is embedded within AI technologies from both process (AI development) and product (AI output) perspectives. Next, there is emerging evidence that AI is reinforcing already entrenched health workforce inequities, where certain types of roles are seen as being the domain of certain genders. Finally, AI may disassociate health professionals' interactions with an embodied, agentic patient by diverting attention to a gendered digital twin. IMPLICATIONS: Responding to these concerns is not simply a matter of teaching about bias but needs to promote an understanding of AI as a sociotechnical phenomenon. Healthcare curricula could usefully provide clinically relevant educational experiences that illustrate how AI intersects with inequitable gendered knowledge practices. Students can be directed to: (1) explore doubts when working with AI-generated data or decisions; (2) refocus on caring through prioritising embodied connections; and (3) consider how to negotiate gendered workplaces in a time of AI.
conclusionThe intersection of gender equity and AI provides an accessible, illustrative case about how changing knowledge practices have the potential to embed inequity and how health professional education programmes might respond.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.